Building performance is influenced by occupants´ presence and actions. Knowledge of
occupants´ future presence and behaviour in buildings is of central importance to the
implementation efforts concerning predictive building systems control strategies.
Specifically, prediction of occupants´ presence in office buildings represents a necessary
condition for predicting their interactions with building systems. In the present contribution,
we focus on evaluation of probabilistic occupancy models to explore the potential of using
past monitored data in predicting future presence of occupants. Towards this end, we
selected a university campus office area, which is equipped with a monitoring infrastructure
and includes a number of open and closed offices. For the purpose of this study, we use
monitored occupancy data and a previously developed stochastic occupancy model to
predict the occupancy profiles on a daily basis. The predictions are then evaluated via
comparison with monitored daily occupancy profiles. To conduct the model evaluation in a
rigorous manner, a number of specific evaluation statistics were deployed. In general, the
obtained level of predictive accuracy of the studied model was found to be rather low,
which reveals the necessity of considering other approaches in modelling occupants´
presence (including non-probabilistic methods) for incorporation in predictive building
systems control.